Financial hardship among patients suffering from neglected tropical diseases: A systematic review and meta-analysis of global literature

Introduction Neglected tropical diseases (NTDs) mainly affect underprivileged populations, potentially resulting in catastrophic health spending (CHS) and impoverishment from out-of-pocket (OOP) costs. This systematic review aimed to summarize the financial hardship caused by NTDs. Methods We searched PubMed, EMBASE, EconLit, OpenGrey, and EBSCO Open Dissertations, for articles reporting financial hardship caused by NTDs from database inception to January 1, 2023. We summarized the study findings and methodological characteristics. Meta-analyses were performed to pool the prevalence of CHS. Heterogeneity was evaluated using the I2 statistic. Results Ten out of 1,768 studies were included, assessing CHS (n = 10) and impoverishment (n = 1) among 2,761 patients with six NTDs (Buruli ulcer, chikungunya, dengue, visceral leishmaniasis, leprosy, and lymphatic filariasis). CHS was defined differently across studies. Prevalence of CHS due to OOP costs was relatively low among patients with leprosy (0.0–11.0%), dengue (12.5%), and lymphatic filariasis (0.0–23.0%), and relatively high among patients with Buruli ulcers (45.6%). Prevalence of CHS varied widely among patients with chikungunya (11.9–99.3%) and visceral leishmaniasis (24.6–91.8%). Meta-analysis showed that the pooled prevalence of CHS due to OOP costs of visceral leishmaniasis was 73% (95% CI; 65–80%, n = 2, I2 = 0.00%). Costs of visceral leishmaniasis impoverished 20–26% of the 61 households investigated, depending on the costs captured. The reported costs did not capture the financial burden hidden by the abandonment of seeking healthcare. Conclusion NTDs lead to a substantial number of households facing financial hardship. However, financial hardship caused by NTDs was not comprehensively evaluated in the literature. To develop evidence-informed strategies to minimize the financial hardship caused by NTDs, studies should evaluate the factors contributing to financial hardship across household characteristics, disease stages, and treatment-seeking behaviors.


Introduction
In 2021, the World Health Organization (WHO) reported that 1.65 billion people required treatment and care for neglected tropical diseases (NTDs) as they faced humanistic, social, and economic burdens incurred by the diseases.NTDs are a diverse group of diseases that mainly affect underprivileged communities in tropical and subtropical areas [1].NTDs predominantly affect disadvantaged populations in low-and middle-income countries (LMICs) due to the lack of timely access to affordable care.It has been reported that every low-income country is affected by at least five NTDs [2].Even worse, impoverishment serves as a structural determinant.At the same time, it is a consequence of NTDs due to the direct and indirect costs incurred [3].Therefore, the WHO has advocated in their recent NTDs 2021-2023 roadmap that NTDs must be overcome to attain Sustainable Development Goals (SDGs) and ensure Universal Health Coverage (UHC).The NTDs 2021-2030 roadmap targets that 90% of the population at risk are protected against catastrophic out-of-pocket (OOP) health spending caused by NTDs [1].
Financial hardship is usually quantified as catastrophic health spending (CHS) (as known as catastrophic health expenditure) and impoverishment.CHS is the proportion of households with OOP costs incurred by a specific disease that exceed a specific threshold of the total household income or expenditure (budget share approach) or non-subsistent household expenditure (capacity-to-pay approach).Impoverishment is when the OOP costs push households below the poverty line [4][5][6].CHS and impoverishment are well-established indicators for the financial risk protection of the healthcare system, which was an essential dimension of the UHC as indicated under the SDG 3.8.2indicators [1,7].
Financial hardship poses a greater challenge for individuals affected by NTDs, as they frequently reside in poverty before the onset of the disease.To evaluate the long-term economic risk imposed by health spending on NTDs, it is important to understand the coping strategies of this population.Literature has shown that coping strategies, such as seeking financial assistance through loans or selling their assets, could push households into or further into poverty if it impacts their productivity [8].Thus, providing coverage to these groups effectively strengthens the financial risk protection of the health system [7].Since some types of NTD are closely related to financial hardship, improving their financial protection may help attain UHC, especially for LMICs [9].
Financial protection is an essential indicator for NTDs and UHC; however, there was limited research on the financial hardship of NTDs.Although many studies addressed the question of the economic burden of NTDs, there is no systematic review and meta-analysis summarizing the financial hardship faced by the population affected by NTDs.Therefore, to fill this knowledge gap and build a baseline for the NTDs roadmap's financial risk protection indicator, this study aimed to summarize the prevalence and magnitude of financial hardship among patients suffering from NTDs.Additionally, we assessed the methodologies of quantifying CHS and impoverishment incurred by NTDs.

Scope of the review
The protocol of this systematic review was registered with PROSPERO (CRD42023385627) [10].This study was reported following the 2020 Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline (S1 PRISMA Checklist) [11].Differences from the original review protocol are described with rationale (S1 Table ).
Outcomes of interest of this systematic review were the prevalence and magnitude of victims who faced financial hardship caused by NTDs, including CHS, impoverishment, and coping strategies.

Search strategy and selection process
We searched three bibliographic databases, PubMed, EMBASE, and EconLit, to identify articles reporting financial hardship among patients suffering from NTDs from any country indexed from database inception to January 1, 2023.We also searched for grey literature in two databases, OpenGrey and EBSCO Open Dissertations.The search terms used were (Disease name and its synonyms) AND (catastroph* OR impoverish* OR coping OR economic consequence* OR out-of-pocket OR "out of pocket" OR ((household OR family OR patient AND (cost* OR spending OR expen*))), that was adapted to match the search techniques of each database.A full search strategy is shown in S2 Table .There was no language restriction applied in this systematic review.A supplemental search was performed by tracking citation and snowballing the eligible articles' reference list.
Two reviewers (CP and JYC) independently performed the study selection.They screened the titles and abstracts of identified articles from database searches for relevance.Potentially relevant articles were sought for full-text articles.We requested the authors for full-text articles or reports of highly relevant articles without full-text articles, such as conference abstracts.The retrieved full-text articles were selected based on the eligibility criteria.Discrepancies arising during study selection were resolved by discussion with the third reviewer (NC).

Eligibility criteria
We included empirical studies reporting CHS, impoverishment, or coping strategies incurred by NTDs using primary data collection.

Data extraction
We developed a data extraction sheet by performing a pilot test of extracting five randomly selected articles and refining it until finalization.Two reviewers (CP and JYC) independently performed data extraction.Another reviewer (JH) checked the extracted data for correctness.Any discrepancies were resolved by discussion among reviewers.
Study findings and methodological characteristics extracted from the eligible articles are as follows: first author, publication year, NTDs, study setting, study design, sample characteristics, sample size, data collection period, data collection methods, time horizon, a perspective of the analysis, discount rate, costing year, reported currency, cost units, the definition of CHS and impoverishment, prevalence and magnitude of CHS and impoverishment incurred, economic consequences and coping strategies of financial hardship.Corresponding authors of the eligible articles were contacted to request individual patient-level data.However, we received no response.
The financial risk protection metric is intended to capture only the OOP costs for medical services (e.g., treatment and diagnosis costs).However, some studies considered certain types of direct non-medical costs (e.g., transportation, food, and accommodation costs) and indirect costs (e.g., productivity and income losses) when quantifying financial hardship.Some studies also included informal care costs, such as traditional medicine, as OOP costs [6].Thus, our systematic review categorized costs extracted from the eligible studies as direct costs (OOP costs) and indirect costs.Direct costs were further categorized as direct medical costs and direct non-medical costs.The combination of direct costs and indirect costs was categorized as total costs.

Quality assessment
Two reviewers independently assessed the eligible articles' quality (CP and JYC).Any discrepancies were resolved by consensus among the reviewers.To the best of our knowledge, there is no risk-of-bias assessment tool for economic burden studies.Hence, we assessed the quality of the eligible articles using the cost-of-illness evaluation checklist by Larg and Moss [13].

Data synthesis
A narrative synthesis was performed to summarize study findings, methodological characteristics, and the quality of the eligible studies.The identified countries were categorized based on the World Bank's income levels and regions [14].

Statistical analysis
We performed meta-analyses to calculate the pooled prevalence of households experiencing financial hardship.However, this was possible only for studies that quantified financial hardship using the same measurement definition for a particular NTD.For example, we performed a meta-analysis to calculate the pooled prevalence of households experiencing CHS due to visceral leishmaniasis based on two studies that defined CHS as direct costs exceeding 10% of annual household income [8,15].The remaining studies were not meta-analyzed due to the differences in the definitions of CHS.We estimated the pooled prevalence of CHS and 95% confidence intervals (CI) using a random-effects model under the DerSimonian and Laird approach [16].Effect sizes were computed using each study's Freeman-Tukey double-arcsinetransformed proportion.This variance-stabilizing transformation is particularly preferable when the proportions are close to 0 or 1 [17].p < .05 was considered statistically significant in 2-sided tests.
Heterogeneity was evaluated by observing the forest plots and using the I 2 statistic that estimated the proportion of variability in a meta-analysis that is explained by differences between the included trials rather than by sampling error.Subgroup analyses were performed to explore possible causes of heterogeneity among study results.Publication bias was assessed using the funnel plot asymmetry test and the Egger regression asymmetry test [18].Statistical analyses were conducted using Stata version 18.0 (Stata Corporation).

Patient and public involvement
Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.
The health insurance systems or special programs covered some of the costs.The costs for diagnosis and treatment of visceral leishmaniasis were provided free of charge to patients under the publicly financed health insurance system in Nepal [8,25] and Sudan [15].In Nigeria, international development partners funded a special program that provided free diagnosis and treatment of Buruli ulcers, as well as accommodation, school funding, and basic allowance [20].Additionally, the Indian government had a special program that provides financial assistance to families of patients affected by leprosy [19].However, patients in India had to pay high OOP costs for medical services for leprosy [19,23], chikungunya [21,26], and lymphatic filariasis [24].Similarly, patients in Vietnam also paid high OOP costs for the medical treatment of dengue [22].For more details, refer to Table 3.

Financial hardship among patients suffering from NTDs
Catastrophic health spending.CHS was variedly defined across studies in terms of types of costs (medical costs, medical and transportation costs, direct costs, indirect costs, or total costs), thresholds (5%, 10%, 15%, 25%, 30%, 40%, or 100%), timeframe (monthly, quarterly, or annual), household resources (income, consumption expenditure, national average annual household expenditure, or international poverty line) and perspective (household or individual).All studies used the budget share approach to quantify CHS.The most commonly used definitions of CHS caused by NTDs were direct costs of a disease episode exceeding 10% of annual household income (3 studies) [8,15,20] and total costs of a disease episode exceeding 10% of annual household income (3 studies) [8,15,25].CHS that included only the direct medical costs was reported in two studies [8,22].
Meta-analyses were performed to pool the prevalence of CHS in studies reporting CHS using the same measurement definition in a particular CHS.This was only possible for visceral leishmaniasis, in which CHS was quantified as direct costs of a disease episode exceeding 10% of annual household income in two studies [8,15], and total costs exceeding 10% of annual household income in three studies [8,15,25].
The pooled prevalence of CHS, defined as direct costs exceeding 10% of annual household income, was 73% (95% CI; 65-80%, n = 2, I 2 = 0.00%), as shown in  The pooled prevalence of CHS, defined as total costs exceeding 10% of annual household income, was 74% (95% CI; 49-93%, n = 3, I 2 = 94.72%), as shown in S2 Fig.We explored the source of heterogeneity by visual inspection of the forest plot.We found that the source of heterogeneity was the differences in the treatment of visceral leishmaniasis, where sodium stibogluconate was used in two studies [8,15], and miltefosine in one study [25].Therefore, we performed a subgroup meta-analysis based on different treatments, as shown in Fig 2B .We removed one study [25] from the meta-analysis to investigate the publication bias without the presence of heterogeneity.Egger's test (P = 0.81) indicated no evidence of small-study effects.Visual inspection of the funnel plot indicated no evidence of publication bias (S1B Fig) .Impoverishment.Impoverishment was investigated in one study in patients with visceral leishmaniasis, which defined impoverishment as annual household income falling below the poverty line after paying for treatment [8].Costs of visceral leishmaniasis impoverished 20-26% of the 61 households investigated, depending on the costs captured (20% medical costs, 21% medical and transportation costs, 26% direct costs), as shown in Table 2.

Coping strategies
Four studies reported coping strategies used by patients to pay the costs of NTDs.These strategies included using savings (71-100% of patients), taking out loans (32-80%), selling livestock or other assets (17-32%), or borrowing money (0-23%), as shown in Table 2.However, these studies did not distinguish between coping strategies used by patients who experienced CHS and those who did not [8,19,24,25].

Cost drivers and determinants of financial hardship
To understand the cost drivers of financial hardship caused by NTDs, we analyzed the percentage share of types of costs captured in the direct costs.The findings are presented in Fig 3 .Direct medical costs were the primary cost driver in nine studies [8,[19][20][21][23][24][25][26].However, one study identified food and transportation costs as the main cost drivers [15].
Determinants of CHS were assessed in one study among patients with Buruli ulcers.The study concluded that neither age, gender, rural/urban location, education, occupation, religion, nor patient income group was a determinant of CHS [20].There was no study investigating determinants of impoverishment.

Discussion
NTDs primarily impact populations with limited financial means, yet the literature addressing the financial hardship caused by NTDs is relatively scarce.Our systematic review revealed that there were only ten studies covering six NTDs.We discovered that many households are facing financial hardship as a result of NTDs, despite having access to publicly funded healthcare systems or special NTD programs.The costs related to NTDs resulted in significant financial hardship for these households, mainly due to the high OOP costs associated with medical treatment.Even in situations where drugs used to treat NTDs were provided free of charge, the costs for supportive care, medical procedures, transportation, and food were still high and could have a devastating financial impact on these households.Moreover, these financial hardship indicators might not fully reflect the financial risk of the population affected by NTDs because many live in poverty or even extreme poverty.Victims of NTDs are usually those who are socially disadvantaged.They need to make trade-offs between suffering from the disease and seeking healthcare because not all victims can afford the costs of NTDs, especially OOP costs for medical treatment and transportation, which could lead to the abandonment of healthcare [1][2][3].
The research findings have shown that merely providing funding for treatments of NTDs is insufficient for protecting those affected by NTDs from financial hardship.Therefore, it is crucial to strengthen the entire healthcare system to effectively address the challenges of NTDs and provide financial protection to the victims.Additionally, it is important to encourage and engage communities to change the behavior of those affected by NTDs so that they seek medical assistance at appropriate healthcare facilities instead of relying on traditional healers or not seeking care at all.Our research also supports the need for an economic framework to guide NTD investments [27].The ability to prioritize investments, informed partially by economic parameters, may appeal to a broad set of stakeholders and help facilitate the process of building coalitions to achieve the WHO's goal that 90% of the at-risk population is protected against financial hardship caused by NTDs [1].
Although there is no consensus regarding the estimation approach and thresholds in quantifying CHS, it is important to note that these differences can significantly impact the findings and consequently impact the applications and implications of the findings [6,28].We found that CHS was variedly defined across studies in terms of estimation approach, types of costs, thresholds, timeframe, household resources, and perspective.Our review revealed that 90% of the included studies captured direct non-medical costs as part of the OOP costs [8,15,[19][20][21][23][24][25][26].Furthermore, Seventy percent of the included studies considered indirect costs in quantifying financial hardship [8,15,19,21,23,25,26].This approach aligned with an indicator called "catastrophic costs" that has emerged in tuberculosis studies.Catastrophic costs occur when the total healthcare costs, including direct and indirect costs, exceed 20% of the annual household income [28].This indicator could be a more comprehensive measure of the overall financial burden of NTDs on the household beyond just the OOP costs which will be useful when evaluating and monitoring different healthcare policies and interventions to mitigate financial hardship caused by NTDs.
The findings of this systematic review and meta-analysis should be interpreted under the following limitations.The included studies in our review only focused on patients who sought healthcare, so the financial burden of those who did not seek healthcare was not captured in the reported OOP costs.This means that people who could not afford healthcare may have been excluded from these studies.Moreover, we could not perform meta-analyses of the prevalence of CHS on all identified NTDs due to differences in how CHS was quantified across studies and lack of access to individual patient-level data.
Hence, we highlighted some methodological considerations to guide future studies on financial hardship among households suffering from NTDs to gain a better understanding of the neglected public health issues and to inform the development of strategies of what to address to tackle the financial burden of NTDs.Firstly, methods to quantify financial hardship should be coherent to allow comparability across studies.For instance, CHS and impoverishment should be defined and measured in a relevant manner to the nature of the NTD, including estimation approach, thresholds, types of costs, timeframe, household resources, and perspective.Secondly, subgroup analyses should be conducted to evaluate the determinants of financial hardship across household characteristics (e.g., income, socioeconomic status) or phases of disease (e.g., disease onset, treatment seeking, diagnosis, treatment, post-treatment).Lastly, coping strategies should be assessed among those who did and did not experience financial hardship to understand the economic consequences of financial hardship across subgroups.

Conclusion
NTDs can be a devastating burden on households, not only in terms of physical and mental health but also financially.NTDs lead to a substantial number of households facing financial hardship.However, financial hardship caused by NTDs was not comprehensively evaluated in the literature.Furthermore, OOP costs represented only a partial picture of the financial hardship the population affected by NTDs faces.To mitigate this financial hardship, it is imperative to conduct thorough research to identify the factors contributing to it.Future research should consider various household characteristics, such as income, education level, and geographic location, as well as the different disease stages, from onset to treatment completion.Future studies should also investigate the hidden financial burden due to the abandonment of healthcare-seeking to capture the economic burden and opportunity costs of those who did not seek healthcare.By carefully examining these factors, researchers and decision-makers can gain insight into the specific challenges faced by households affected by NTDs and develop targeted interventions to alleviate financial hardships.Ultimately, these studies can help inform the development of strategies to reduce the burden of NTDs on households and improve overall health outcomes.